It is really hard to get through articles with prose this bad. I don't know if it's because of LLM help or lack of practice, but man i have tried 3 times now to get through it and just can't.
> According to the empirical literature on deskilling, automation bias, and skill decay, many professionals rely on artificial intelligence much more than is necessary when it is available, and the effects of such overreliance on skill decay are unlikely to be entirely understood by the professionals themselves. I argue that this – what I call the insidious nature of deskilling – supports a normative view, according to which the responsibility for tackling deskilling should not be ascribed to the individual professional but the risks of professional deskilling should be tackled by the professional community instead. Mitigating the risks of deskilling should start from an intra-field analysis of the core skills of the profession that should not be outsourced to artificial intelligence. Then, the individual professional would not be left alone to determine how and when to prevent deskilling during the adoption of artificial intelligence within her profession.
Yes, I read the article, although I appreciate your manner of suggesting i haven't over what it could have been. And again - the responsibility for making poor choices and over-reliance on AI lies with the individual, regardless of what the article says. This is like saying that responsibility for being able to do mental math should be tackled by the professional community because calculators exist, or that the professional chef community needs to get involved to prevent a devolution of skills due to this new-fangled micro-wave oven.
It didn't seem like it, because section 2 directly discusses the issue you raised and why individuals aren't in a position to adequately prevent deskilling on by themselves. OK, you disagree with it, but you don't even engage with the actual argument it makes.
Just because individuals may not be fully aware of the consequences of their actions does not make them suddenly not responsible for them. See for example not studying well in college, eating poorly, not exercising, walking around barefoot in hookworm country, leaving food out while camping in bear country, and swimming without underwear in candiru-infested rivers.
While this may be the prevailing POV in the present, it certainly wasn't always this way. Expressive individualism is an anomaly in the grand scheme of human history.
Many things that we treasure are anomalies in the grand scheme of human history. Treating other races as human beings, valuing life and human potential, believing that everyone including women should be educated... How's that appeal to historical authority apply in those cases? Perhaps you're also a monarchist? In which case, my bad, at least you're consistent :)
You're lucky. Every single person (n of around 10) I've been unlucky enough to review code for lost between 0.5 and 3 promotion levels of competence when they started using LLM code generation, and it's been worse for the better programmers because they have more capacity to lose skills.
My personal "favorite" was when the lead engineer who onboarded me half a decade prior forgot the written policy he'd put in place of "no raw js dates. use this library for everything date related instead" and sent up an MR that not only used javascript dates, but did complex operations on them (incorrectly at that, because it didn't account for timezones, daylight saving, years that had a leap day, and months that weren't 30 days).
From what I can tell, it's the exact same reason people drive faster than is prudent or use their cellphone while driving. It feels safe and good right up until it isn't and you crash. And because most places don't have anywhere close to adequate specification detail, test coverage, or review coverage, the broken bits aren't even noticed until much later.
I think for a lot of people it's that they stopped caring or obsessing over the (perceived) small details; AI makes it very easy to work on a higher level. I suspect (don't quote me on this) that it's the same for a lot of developers that grew to more lead / managerial positions - at some point the details don't matter much to you personally and you need to spend your energy elsewhere.
But I hope people are gathering metrics. We had an extra meeting the other day because we're seeing an upwards trend in outages, the meeting was mainly about how it affects various departments (like customer support) and potential revenue loss (can't sell a product/service if the signup page is down for three days).
Thing is, there's no one cause for any of those - we have hundreds of engineers, dozens of applications and 3rd party integrations, millions of (potential) customers each running their own set of devices, and it's pretty much impossible to control everything.
But this goes beyond whether or not code was written by an attentive hand working under a strict set of policies or an AI that figures it out on the go, and goes up a level to things like realtime monitoring and incident responses.
You're right that as a person moves into management/staff+ that individual details matter less for them, because they begin to deal at a more strategic or operational level, but someone still needs to obsess over the small details (to make things easier, let's assume we're only talking about the details that actually matter and that there's broad agreement what that set is). It's not that those details stop mattering to them, it's that they have to depend on the assumption/promise that someone else is going to mind those details for them, so that they can work on things with a broader perspective.
The problem comes when no one is actually minding those details anymore. If those details aren't actually minded, then the work at the higher levels will be much less useful and effective, and in the worst cases won't matter at all.
I am seeing the same. The skillsets degrading rather rapidly, people not able to maintain focus and becoming less sharp in general. The brain rot associated with short form videos is affecting our industry via LLMs. It doesn't give me any joy to see it happening, especially to people I care about.
I don't know why I haven't been able to see the similarity between short form content and LLMs in our industry until reading your comment, but that is apt. That's the impression I'm getting. I stay away from "agentic code generation" as much as possible, just like I avoid short form content mills like the plague. That said, LLMs have been a huge boon for me as a research assistant. Being able to look up very niche problems, and have responses be tailored to me, is awesome. My brain stays sharp and I still enjoy the fun of putting the pieces together myself much faster than before.
I don't personally like LLMs for research assistance (yet?) because i can't get over the hallucinating or rather, waste too much time validating that it's not currently overcast when they tell me the sky is in fact blue.
But, especially as code gets flung over the wall faster and with less care, I do think they are getting to be pretty great at reviewing code for specific things that a linter can't easily catch and for looking for security, implementation, and architectural flaws before I have to look for them. A couple examples of what i mean: 'does the code use knex.raw with a template literal?', 'does the code do n+1 db lookups instead of something better?' 'do all the added/modified tests follow the test case template defined here?'
> But there was never a general principle about scale and automation articulated in the Constitution because it just wasn't a thing to worry about in the 1700s.
> We're left to hope that courts agree that just because something is okay for one police officer in one place to do, that doesn't mean the police department can perform that same task a thousand times in a thousand places with a thousand machines and still have it be okay.
There are multiple court cases that have done this exactly this. Carpenter v. United States and Chatrie v. United States are the ones you want.
This doesn't follow. We've had code as trusted as that for _decades_. Common criteria and EAL was certified at the end of the 20th century. Before that there was the rainbow series in the US dating back to the 1980s [1].
It's absolutely cool to see this sort of validation process get cheaper and easier, but it means nothing if no one cares enough to do it. EAL1 certification can be as cheap as a beefy server, but it's not commonly done because effectively no one cares.
As microsoft learned with the zune just because it's cheaper or better at the same price doesn't mean anyone will use it. Culturally, we have to make the effort of verifying code worth it.
When you're learning/internalizing existing knowledge, you tread a defined path skipping unnecessary stops and diversion and heading instead directly to the destination. The destination, not the journey, is the point.
When you're discovering new knowledge in the form of proving/disproving, there's no defined path to follow, so there can be quite a bit of backtracking and diversions and detours into other areas you weren't planning on going initially and while there might be some well-defined paths to follow, you might have to cut your own path through uncharted desert or jungle.
All those diversions and detours make the journey just as if not more important than the destination because they create new destinations of their own for future travel that would not have been spotted or noticed for a while longer (if ever) otherwise.
So to bring it back to math, transitioning from having to develop proofs for theorems to validating/learning extant proofs completely changes the scope of future discovery. Everyone will tread the exact same path to a proof/theorem and then stand in the same place to look for future destinations and then use AI to build them a path to that new destination and then everyone will follow the same path to the new destination and repeat the process, so the chances of finding something curious along the way plummets. And something curious could be an entirely new field of math, or maybe just a new problem that isn't relevant to the intended destination but gives a view of many new never before seen destinations for future trips.
As much as it sucks for the ecosystem that's built itself up around the world wide web, good ad blockers and fingerprinting protection are as important as firewalls and antiviruses now. There's no more babies in this fetid bathwater.
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